






from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_torch_available,
    is_vision_available,
)


SCREAMING_SNAKE_CASE__		:							Dict 				=				{
    """configuration_convnext""": ["""CONVNEXT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """ConvNextConfig""", """ConvNextOnnxConfig"""]
}

try:
      if not is_vision_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      SCREAMING_SNAKE_CASE__		:							Dict 				=				["""ConvNextFeatureExtractor"""]
      SCREAMING_SNAKE_CASE__		:							Tuple 				=				["""ConvNextImageProcessor"""]

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      SCREAMING_SNAKE_CASE__		:							str 				=				[
          """CONVNEXT_PRETRAINED_MODEL_ARCHIVE_LIST""",
          """ConvNextForImageClassification""",
          """ConvNextModel""",
          """ConvNextPreTrainedModel""",
          """ConvNextBackbone""",
      ]

try:
      if not is_tf_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      SCREAMING_SNAKE_CASE__		:							int 				=				[
          """TFConvNextForImageClassification""",
          """TFConvNextModel""",
          """TFConvNextPreTrainedModel""",
      ]

if TYPE_CHECKING:
      from .configuration_convnext import CONVNEXT_PRETRAINED_CONFIG_ARCHIVE_MAP, ConvNextConfig, ConvNextOnnxConfig

      try:
            if not is_vision_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .feature_extraction_convnext import ConvNextFeatureExtractor
            from .image_processing_convnext import ConvNextImageProcessor

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_convnext import (
                CONVNEXT_PRETRAINED_MODEL_ARCHIVE_LIST,
                ConvNextBackbone,
                ConvNextForImageClassification,
                ConvNextModel,
                ConvNextPreTrainedModel,
            )

      try:
            if not is_tf_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_tf_convnext import TFConvNextForImageClassification, TFConvNextModel, TFConvNextPreTrainedModel


else:
      import sys

      SCREAMING_SNAKE_CASE__		:							str 				=				_LazyModule(__name__, globals()["""__file__"""], _import_structure)











'''simple docstring'''






import json
import os
import re
import unittest

from transformers import CodeGenTokenizer, CodeGenTokenizerFast
from transformers.models.codegen.tokenization_codegen import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin

@require_tokenizers
class 				a__(   lowerCamelCase__						,					unittest.TestCase      ):
    lowercase__					=       CodeGenTokenizer
    lowercase__					=       CodeGenTokenizerFast
    lowercase__					=       True
    lowercase__					=       {"""add_prefix_space""": True}
    lowercase__					=       False







    def      lowercase_			( self					:    List[str]      ):
      super().setUp()

      # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
      a		:   Any	  =	[
          'l',
          'o',
          'w',
          'e',
          'r',
          's',
          't',
          'i',
          'd',
          'n',
          '\u0120',
          '\u0120l',
          '\u0120n',
          '\u0120lo',
          '\u0120low',
          'er',
          '\u0120lowest',
          '\u0120newer',
          '\u0120wider',
          '<unk>',
          '<|endoftext|>',
      ]
      a		:   Dict	  =	dict(zip(__snake_case		,     range(len(__snake_case      )      )      )      )
      a		:   str	  =	['#version: 0.2', '\u0120 l', '\u0120l o', '\u0120lo w', 'e r', '']
      a		:   List[str]	  =	{'unk_token': '<unk>'}

      a		:   List[str]	  =	os.path.join(self.tmpdirname		,     VOCAB_FILES_NAMES['vocab_file']      )
      a		:   Dict	  =	os.path.join(self.tmpdirname		,     VOCAB_FILES_NAMES['merges_file']      )
      with open(self.vocab_file		,     'w'		,     encoding='utf-8'      ) as fp:
        fp.write(json.dumps(__snake_case      ) + '\n'      )
      with open(self.merges_file		,     'w'		,     encoding='utf-8'      ) as fp:
        fp.write('\n'.join(__snake_case      )      )







    def      lowercase_			( self					:    Tuple		,     **__snake_case					:    Dict      ):
      kwargs.update(self.special_tokens_map      )
      return CodeGenTokenizer.from_pretrained(self.tmpdirname		,     **__snake_case      )







    def      lowercase_			( self					:    List[Any]		,     **__snake_case					:    List[str]      ):
      kwargs.update(self.special_tokens_map      )
      return CodeGenTokenizerFast.from_pretrained(self.tmpdirname		,     **__snake_case      )







    def      lowercase_			( self					:    Optional[int]		,     __snake_case					:    List[Any]      ):
      a		:   Tuple	  =	'lower newer'
      a		:   str	  =	'lower newer'
      return input_text, output_text







    def      lowercase_			( self					:    str      ):
      a		:   List[Any]	  =	CodeGenTokenizer(self.vocab_file		,     self.merges_file		,     **self.special_tokens_map      )
      a		:   Dict	  =	'lower newer'
      a		:   int	  =	['\u0120low', 'er', '\u0120', 'n', 'e', 'w', 'er']
      a		:   List[str]	  =	tokenizer.tokenize(__snake_case		,     add_prefix_space=__snake_case      )
      self.assertListEqual(__snake_case		,     __snake_case      )

      a		:   Dict	  =	tokens + [tokenizer.unk_token]
      a		:   int	  =	[14, 15, 10, 9, 3, 2, 15, 19]
      self.assertListEqual(tokenizer.convert_tokens_to_ids(__snake_case      )		,     __snake_case      )







    def      lowercase_			( self					:    List[Any]      ):
      if not self.test_rust_tokenizer:
        return

      a		:   Optional[int]	  =	self.get_tokenizer()
      a		:   Tuple	  =	self.get_rust_tokenizer(add_prefix_space=__snake_case      )

      a		:   List[str]	  =	'lower newer'

      # Testing tokenization
      a		:   Optional[int]	  =	tokenizer.tokenize(__snake_case		,     add_prefix_space=__snake_case      )
      a		:   Optional[Any]	  =	rust_tokenizer.tokenize(__snake_case      )
      self.assertListEqual(__snake_case		,     __snake_case      )

      # Testing conversion to ids without special tokens
      a		:   Tuple	  =	tokenizer.encode(__snake_case		,     add_special_tokens=__snake_case		,     add_prefix_space=__snake_case      )
      a		:   str	  =	rust_tokenizer.encode(__snake_case		,     add_special_tokens=__snake_case      )
      self.assertListEqual(__snake_case		,     __snake_case      )

      # Testing conversion to ids with special tokens
      a		:   Optional[int]	  =	self.get_rust_tokenizer(add_prefix_space=__snake_case      )
      a		:   Optional[int]	  =	tokenizer.encode(__snake_case		,     add_prefix_space=__snake_case      )
      a		:   Dict	  =	rust_tokenizer.encode(__snake_case      )
      self.assertListEqual(__snake_case		,     __snake_case      )

      # Testing the unknown token
      a		:   Any	  =	tokens + [rust_tokenizer.unk_token]
      a		:   List[Any]	  =	[14, 15, 10, 9, 3, 2, 15, 19]
      self.assertListEqual(rust_tokenizer.convert_tokens_to_ids(__snake_case      )		,     __snake_case      )







    def      lowercase_			( self					:    List[str]		,     *__snake_case					:    int		,     **__snake_case					:    str      ):
      # It's very difficult to mix/test pretokenization with byte-level
      # And get both CodeGen and Roberta to work at the same time (mostly an issue of adding a space before the string)
      pass







    def      lowercase_			( self					:    List[str]		,     __snake_case					:    str=15      ):
      for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
        with self.subTest(F"""{tokenizer.__class__.__name__} ({pretrained_name})"""      ):
          a		:   List[Any]	  =	self.rust_tokenizer_class.from_pretrained(__snake_case		,     **__snake_case      )

          # Simple input
          a		:   Dict	  =	'This is a simple input'
          a		:   int	  =	['This is a simple input 1', 'This is a simple input 2']
          a		:   Dict	  =	('This is a simple input', 'This is a pair')
          a		:   Dict	  =	[
              ('This is a simple input 1', 'This is a simple input 2'),
              ('This is a simple pair 1', 'This is a simple pair 2'),
          ]

          # Simple input tests
          self.assertRaises(__snake_case		,     tokenizer_r.encode		,     __snake_case		,     max_length=__snake_case		,     padding='max_length'      )

          # Simple input
          self.assertRaises(__snake_case		,     tokenizer_r.encode_plus		,     __snake_case		,     max_length=__snake_case		,     padding='max_length'      )

          # Simple input
          self.assertRaises(
              __snake_case		,     tokenizer_r.batch_encode_plus		,     __snake_case		,     max_length=__snake_case		,     padding='max_length'		,     )

          # Pair input
          self.assertRaises(__snake_case		,     tokenizer_r.encode		,     __snake_case		,     max_length=__snake_case		,     padding='max_length'      )

          # Pair input
          self.assertRaises(__snake_case		,     tokenizer_r.encode_plus		,     __snake_case		,     max_length=__snake_case		,     padding='max_length'      )

          # Pair input
          self.assertRaises(
              __snake_case		,     tokenizer_r.batch_encode_plus		,     __snake_case		,     max_length=__snake_case		,     padding='max_length'		,     )







    def      lowercase_			( self					:    Optional[Any]      ):
      a		:   Any	  =	CodeGenTokenizer.from_pretrained(self.tmpdirname		,     pad_token='<pad>'      )

      # Simple input
      a		:   Union[str, Any]	  =	'This is a simple input'
      a		:   Dict	  =	['This is a simple input looooooooong', 'This is a simple input']
      a		:   int	  =	('This is a simple input', 'This is a pair')
      a		:   List[Any]	  =	[
          ('This is a simple input loooooong', 'This is a simple input'),
          ('This is a simple pair loooooong', 'This is a simple pair'),
      ]

      a		:   Optional[int]	  =	tokenizer.pad_token_id

      a		:   List[Any]	  =	tokenizer(__snake_case		,     padding='max_length'		,     max_length=30		,     return_tensors='np'      )
      a		:   Union[str, Any]	  =	tokenizer(__snake_case		,     padding=__snake_case		,     truncate=__snake_case		,     return_tensors='np'      )
      a		:   Optional[Any]	  =	tokenizer(*__snake_case		,     padding='max_length'		,     max_length=60		,     return_tensors='np'      )
      a		:   List[Any]	  =	tokenizer(__snake_case		,     padding=__snake_case		,     truncate=__snake_case		,     return_tensors='np'      )

      # s
      # test single string max_length padding
      self.assertEqual(out_s['input_ids'].shape[-1]		,     30      )
      self.assertTrue(pad_token_id in out_s['input_ids']      )
      self.assertTrue(0 in out_s['attention_mask']      )

      # s2
      # test automatic padding
      self.assertEqual(out_sa['input_ids'].shape[-1]		,     33      )
      # long slice doesn't have padding
      self.assertFalse(pad_token_id in out_sa['input_ids'][0]      )
      self.assertFalse(0 in out_sa['attention_mask'][0]      )
      # short slice does have padding
      self.assertTrue(pad_token_id in out_sa['input_ids'][1]      )
      self.assertTrue(0 in out_sa['attention_mask'][1]      )

      # p
      # test single pair max_length padding
      self.assertEqual(out_p['input_ids'].shape[-1]		,     60      )
      self.assertTrue(pad_token_id in out_p['input_ids']      )
      self.assertTrue(0 in out_p['attention_mask']      )

      # p2
      # test automatic padding pair
      self.assertEqual(out_pa['input_ids'].shape[-1]		,     52      )
      # long slice pair doesn't have padding
      self.assertFalse(pad_token_id in out_pa['input_ids'][0]      )
      self.assertFalse(0 in out_pa['attention_mask'][0]      )
      # short slice pair does have padding
      self.assertTrue(pad_token_id in out_pa['input_ids'][1]      )
      self.assertTrue(0 in out_pa['attention_mask'][1]      )







    def      lowercase_			( self					:    Optional[int]      ):
      a		:   int	  =	'$$$'
      a		:   Dict	  =	CodeGenTokenizer.from_pretrained(self.tmpdirname		,     bos_token=__snake_case		,     add_bos_token=__snake_case      )

      a		:   int	  =	'This is a simple input'
      a		:   Tuple	  =	['This is a simple input 1', 'This is a simple input 2']

      a		:   Any	  =	tokenizer.bos_token_id

      a		:   Union[str, Any]	  =	tokenizer(__snake_case      )
      a		:   Dict	  =	tokenizer(__snake_case      )

      self.assertEqual(out_s.input_ids[0]		,     __snake_case      )
      self.assertTrue(all(o[0] == bos_token_id for o in out_sa.input_ids      )      )

      a		:   Optional[Any]	  =	tokenizer.decode(out_s.input_ids      )
      a		:   Optional[Any]	  =	tokenizer.batch_decode(out_sa.input_ids      )

      self.assertEqual(decode_s.split()[0]		,     __snake_case      )
      self.assertTrue(all(d.split()[0] == bos_token for d in decode_sa      )      )







    @slow
    def      lowercase_			( self					:    List[Any]      ):
      a		:   Tuple	  =	CodeGenTokenizer.from_pretrained('Salesforce/codegen-350M-mono'      )

      a		:   Union[str, Any]	  =	'\nif len_a > len_b:\n    result = a\nelse:\n    result = b\n\n\n\n#'
      a		:   Optional[Any]	  =	'\nif len_a > len_b:      result = a\nelse:      result = b'

      a		:   Any	  =	tokenizer.encode(__snake_case      )
      a		:   Union[str, Any]	  =	['^#', re.escape('<|endoftext|>'      ), '^\'\'\'', '^"""', '\n\n\n']
      a		:   List[str]	  =	tokenizer.decode(__snake_case		,     truncate_before_pattern=__snake_case      )
      self.assertEqual(__snake_case		,     __snake_case      )







    def      lowercase_			( self					:    Any      ):
      pass